Database System Concepts, 5th Ed.

©Silberschatz, Korth and Sudarshan

See www.db-book.com for conditions on re-use

Chapter 1: Introduction

©Silberschatz, Korth and Sudarshan1.2Database System Concepts - 5th Edition, Sep 6, 2006

Chapter 1: Introduction

Purpose of Database Systems

View of Data

Database Languages

Relational Databases

Database Design

Object-based and semistructured databases

Data Storage and Querying

Transaction Management

Database Architecture

Database Users and Administrators

Overall Structure

History of Database Systems

©Silberschatz, Korth and Sudarshan1.3Database System Concepts - 5th Edition, Sep 6, 2006

Database Management System (DBMS)

DBMS contains information about a particular enterprise

zCollection of interrelated data

zSet of programs to access the data

zAn environment that is both convenient and efficient to use

Database Applications:

zBanking: all transactions

zAirlines: reservations, schedules

zUniversities: registration, grades

zSales: customers, products, purchases

zOnline retailers: order tracking, customized recommendations

zManufacturing: production, inventory, orders, supply chain

zHuman resources: employee records, salaries, tax deductions

Databases touch all aspects of our lives

©Silberschatz, Korth and Sudarshan1.4Database System Concepts - 5th Edition, Sep 6, 2006

Purpose of Database Systems

In the early days, database applications were built directly on top of

file systems

Drawbacks of using file systems to store data:

zData redundancy and inconsistency

Multiple file formats, duplication of information in different files

zDifficulty in accessing data

Need to write a new program to carry out each new task

zData isolation — multiple files and formats

zIntegrity problems

Integrity constraints (e.g. account balance > 0) become

“buried” in program code rather than being stated explicitly

Hard to add new constraints or change existing ones

©Silberschatz, Korth and Sudarshan1.5Database System Concepts - 5th Edition, Sep 6, 2006

Purpose of Database Systems (Cont.)

Drawbacks of using file systems (cont.)

zAtomicity of updates

Failures may leave database in an inconsistent state with partial

updates carried out

Example: Transfer of funds from one account to another should

either complete or not happen at all

zConcurrent access by multiple users

Concurrent accessed needed for performance

Uncontrolled concurrent accesses can lead to inconsistencies

–Example: Two people reading a balance and updating it at the

same time

zSecurity problems

Hard to provide user access to some, but not all, data

Database systems offer solutions to all the above problems

©Silberschatz, Korth and Sudarshan1.6Database System Concepts - 5th Edition, Sep 6, 2006

Levels of Abstraction

Physical level: describes how a record (e.g., customer) is stored.

Logical level: describes data stored in database, and the relationships

among the data.

type customer = record

customer_id : string;

customer_name : string;

customer_street : string;

customer_city : integer;

end

View level: A way to hide: (a) details of data types and (b) information

(such as an employee’s salary) for security purposes.

©Silberschatz, Korth and Sudarshan1.7Database System Concepts - 5th Edition, Sep 6, 2006

View of Data

An architecture for a database system

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Instances and Schemas

Similar to types and variables in programming languages

Schema – the logical structure of the database

zExample: The database consists of information about a set of customers and

accounts and the relationship between them)

zAnalogous to type information of a variable in a program

zPhysical schema: database design at the physical level

zLogical schema: database design at the logical level

Instance – the actual content of the database at a particular point in time

zAnalogous to the value of a variable

Physical Data Independence – the ability to modify the physical schema without

changing the logical schema

zApplications depend on the logical schema

zIn general, the interfaces between the various levels and components should

be well defined so that changes in some parts do not seriously influence others.

©Silberschatz, Korth and Sudarshan1.9Database System Concepts - 5th Edition, Sep 6, 2006

Data Models

A collection of tools for describing

zData

zData relationships

zData semantics

zData constraints

Relational model

Entity-Relationship data model (mainly for database design)

Object-based data models (Object-oriented and Object-relational)

Semistructured data model (XML)

Other older models:

zNetwork model

zHierarchical model

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Data Manipulation Language (DML)

Language for accessing and manipulating the data organized by the

appropriate data model

zDML also known as query language

Two classes of languages

zProcedural – user specifies what data is required and how to get

those data

zDeclarative (nonprocedural) – user specifies what data is

required without specifying how to get those data

SQL is the most widely used query language

©Silberschatz, Korth and Sudarshan1.11Database System Concepts - 5th Edition, Sep 6, 2006

Data Definition Language (DDL)

Specification notation for defining the database schema

Example: create table account (

account-number char(10),

balance integer)

DDL compiler generates a set of tables stored in a data dictionary

Data dictionary contains metadata (i.e., data about data)

zDatabase schema

zIntegrity constraints

Domain constraints

Referential integrity (references constraint in SQL)

Assertions

zAuthorization

Data storage and definition language

zSpecifies the storage structure and access methods used

©Silberschatz, Korth and Sudarshan1.12Database System Concepts - 5th Edition, Sep 6, 2006

Relational Databases

A relational database is based on the relational data model

Data and relationships among the data is represented by a

collection of tables

Includes both a DML and a DDL

Most commercial relational database systems employ the SQL

query langue.

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Relational Model

Example of tabular data in the relational model

Attributes

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A Sample Relational Database

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SQL

SQL: widely used non-procedural language

zExample: Find the name of the customer with customer-id 192-83-7465

select customer.customer_name

from customer

where customer.customer_id = ‘192-83-7465’

zExample: Find the balances of all accounts held by the customer with

customer-id 192-83-7465

select account.balance

from depositor, account

where depositor.customer_id = ‘192-83-7465’ and

depositor.account_number = account.account_number

Application programs generally access databases through one of

zLanguage extensions to allow embedded SQL

zApplication program interface (e.g., ODBC/JDBC) which allow SQL

queries to be sent to a database

©Silberschatz, Korth and Sudarshan1.16Database System Concepts - 5th Edition, Sep 6, 2006

Database Design

The process of designing the general structure of the database:

Logical Design – Deciding on the database schema. Database design

requires that we find a “good” collection of relation schemas.

zBusiness decision – What attributes should we record in the

database?

zComputer Science decision – What relation schemas should we

have and how should the attributes be distributed among the various

relation schemas?

Physical Design – Deciding on the physical layout of the database

©Silberschatz, Korth and Sudarshan1.17Database System Concepts - 5th Edition, Sep 6, 2006

The Entity

The Entity-

-Relationship Model

Relationship Model

Models an enterprise as a collection of entities and relationships

zEntity: a “thing” or “object” in the enterprise that is distinguishable

from other objects

Described by a set of attributes

zRelationship: an association among several entities

Represented diagrammatically by an entity-relationship diagram:

©Silberschatz, Korth and Sudarshan1.18Database System Concepts - 5th Edition, Sep 6, 2006

Object

Object-

-Relational Data Models

Relational Data Models

Extend the relational data model by including object orientation and

constructs to deal with added data types.

Allow attributes of tuples to have complex types, including non-atomic

values such as nested relations.

Preserve relational foundations, in particular the declarative access to

data, while extending modeling power.

Provide upward compatibility with existing relational languages.

©Silberschatz, Korth and Sudarshan1.19Database System Concepts - 5th Edition, Sep 6, 2006

XML: Extensible Markup Language

Defined by the WWW Consortium (W3C)

Originally intended as a document markup language not a

database language

The ability to specify new tags, and to create nested tag structures

made XML a great way to exchange data, not just documents

XML has become the basis for all new generation data interchange

formats.

A wide variety of tools is available for parsing, browsing and

querying XML documents/data

©Silberschatz, Korth and Sudarshan1.20Database System Concepts - 5th Edition, Sep 6, 2006

Storage Management

Storage manager is a program module that provides the interface

between the low-level data stored in the database and the application

programs and queries submitted to the system.

The storage manager is responsible to the following tasks:

zInteraction with the file manager

zEfficient storing, retrieving and updating of data

Issues:

zStorage access

zFile organization

zIndexing and hashing

©Silberschatz, Korth and Sudarshan1.21Database System Concepts - 5th Edition, Sep 6, 2006

Query Processing

1. Parsing and translation

2. Optimization

3. Evaluation

Query Processing (Cont.)

Alternative ways of evaluating a given query

zEquivalent expressions

zDifferent algorithms for each operation

Cost difference between a good and a bad way of evaluating a query can

be enormous

Need to estimate the cost of operations

zDepends critically on statistical information about relations which the

database must maintain

zNeed to estimate statistics for intermediate results to compute cost of

complex expressions

Transaction Management

A transaction is a collection of operations that performs a single

logical function in a database application

Transaction-management component ensures that the database

remains in a consistent (correct) state despite system failures (e.g.,

power failures and operating system crashes) and transaction failures.

Concurrency-control manager controls the interaction among the

concurrent transactions, to ensure the consistency of the database.

Database Architecture

The architecture of a database systems is greatly influenced by

the underlying computer system on which the database is running:

Centralized

Client-server

Parallel (multi-processor)

Distributed

Database Users

Users are differentiated by the way they expect to interact with

the system

Application programmers – interact with system through DML calls

Sophisticated users – form requests in a database query language

Specialized users – write specialized database applications that do

not fit into the traditional data processing framework

Naïve users – invoke one of the permanent application programs that

have been written previously

zExamples, people accessing database over the web, bank tellers,

clerical staff

Database Administrator

Coordinates all the activities of the database system; the

database administrator has a good understanding of the

enterprise’s information resources and needs.

Database administrator's duties include:

zSchema definition

zStorage structure and access method definition

zSchema and physical organization modification

zGranting user authority to access the database

zSpecifying integrity constraints

zActing as liaison with users

zMonitoring performance and responding to changes in

requirements

Overall System Structure

History of Database Systems

1950s and early 1960s:

zData processing using magnetic tapes for storage

Tapes provide only sequential access

zPunched cards for input

Late 1960s and 1970s:

zHard disks allow direct access to data

zNetwork and hierarchical data models in widespread use

zTed Codd defines the relational data model

Would win the ACM Turing Award for this work

IBM Research begins System R prototype

UC Berkeley begins Ingres prototype

zHigh-performance (for the era) transaction processing

History (cont.)

1980s:

zResearch relational prototypes evolve into commercial systems

SQL becomes industrial standard

zParallel and distributed database systems

zObject-oriented database systems

1990s:

zLarge decision support and data-mining applications

zLarge multi-terabyte data warehouses

zEmergence of Web commerce

2000s:

zXML and XQuery standards

zAutomated database administration

Database System Concepts, 5th Ed.

See www.db-book.com for conditions on re-use

End of Chapter 1

Figure 1.4

Figure 1.7